Integrating p53-associated genes and infiltrating immune cell characterization as a prognostic biomarker in multiple myeloma.

Background: Tumor genetic anomalies and immune dysregulation are pivotal in the progression of multiple myeloma (MM). Accurate patient stratification is essential for effective MM management, yet current models fail to comprehensively incorporate both molecular and immune profiles. Methods: We examined 776 samples from the MMRF CoMMpass database, employing univariate regression with LASSO and CIBERSORT algorithms to identify 15 p53-related genes and six immune cells with prognostic significance in MM. A p53-TIC (tumor-infiltrating immune cells) classifier was constructed by calculating scores using the bootstrap-multicox method, which was further validated externally (GSE136337) and through ten-fold internal cross-validation for its predictive reliability and robustness. Results: The p53-TIC classifier demonstrated excellent performance in predicting the prognosis in MM. Specifically, patients in the p53low/TIChigh subgroup had the most favorable prognosis and the lowest tumor mutational burden (TMB). Conversely, those in the p53high/TIClow subgroup, with the least favorable prognosis and the highest TMB, were predicted to have the best anti-PD1 and anti-CTLA4 response rate (40 %), which can be explained by their higher expression of PD1 and CTLA4. The three-year area under the curve (AUC) was 0.80 in the total sample. Conclusions: Our study highlights the potential of an integrated analysis of p53-associated genes and TIC in predicting prognosis and aiding clinical decision-making in MM patients. This finding underscores the significance of comprehending the intricate interplay between genetic abnormalities and immune dysfunction in MM. Further research into this area may lead to the development of more effective treatment strategies.

Essential procedures of single-cell RNA sequencing in multiple myeloma and its translational value.

Multiple myeloma (MM) is a malignant neoplasm characterized by clonal proliferation of abnormal plasma cells. In many countries, it ranks as the second most prevalent malignant neoplasm of the hematopoietic system. Although treatment methods for MM have been continuously improved and the survival of patients has been dramatically prolonged, MM remains an incurable disease with a high probability of recurrence. As such, there are still many challenges to be addressed. One promising approach is single-cell RNA sequencing (scRNA-seq), which can elucidate the transcriptome heterogeneity of individual cells and reveal previously unknown cell types or states in complex tissues. In this review, we outlined the experimental workflow of scRNA-seq in MM, listed some commonly used scRNA-seq platforms and analytical tools. In addition, with the advent of scRNA-seq, many studies have made new progress in the key molecular mechanisms during MM clonal evolution, cell interactions and molecular regulation in the microenvironment, and drug resistance mechanisms in target therapy. We summarized the main findings and sequencing platforms for applying scRNA-seq to MM research and proposed broad directions for targeted therapies based on these findings.

MSC Senescence-Related Genes Are Associated with Myeloma Prognosis and Lipid Metabolism-Mediated Resistance to Proteasome Inhibitors.

Background: Complex carcinogenic mechanisms and the existence of tumour heterogeneity in multiple myeloma (MM) prevent the most commonly used staging system from effectively interpreting the prognosis of patients. Since the microenvironment plays an important role in driving tumour development and MM occurs most often in middle-aged and elderly patients, we hypothesize that ageing of bone marrow mesenchymal stem cells (BM-MSCs) may be associated with the progression of MM. Methods: In this study, we collected the transcriptome data on MM from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Differentially expressed genes in both senescent MSCs and MM tumour cells were considered relevant damaged genes. GO and KEGG analyses were applied for functional evaluation. A PPI network was constructed to identify hub genes. Subsequently, we studied the damaged genes that affected the prognosis of MM. Least absolute shrinkage and selection operator (lasso) regression was used to identify the most important features, and a risk model was created. The reliability of the risk model was evaluated with the other 3 GEO validation cohorts. In addition, ROC analysis was used to evaluate the novel risk model. An analysis of immune checkpoint-related genes, tumour immune dysfunction and exclusion (TIDE), and immunophenotypic scoring (IPS) were performed to assess the immune status of risk groups. pRRophetic was utilized to predict the sensitivity to administration of chemotherapeutic agents. Results: We identified that MAPK, PI3K, and p53 signalling pathways were activated in both senescent MSCs and tumour cells, and we also located hub genes. In addition, we constructed a 14-gene prognostic risk model, which was analysed with the ROC and validated in different datasets. Further analysis revealed significant differences in predicted risk values across the International Staging System (ISS) stage, sex, and 1q21 copy number. A high-risk group with higher immunogenicity was predicted to have low proteasome inhibitor sensitivity and respond poorly to immunotherapy. Lipid metabolism pathways were found to be significantly different between high-risk and low-risk groups. A nomogram was created by combining clinical data, and the optimization model was further improved. Finally, real-time qPCR was used to validate two bortezomib-resistant myeloma cell lines, and the test confirmed that 10 genes were detected to be expressed in resistant cell lines with the same trend as in the high-risk cohort compared to nonresistant cells. Conclusion: Fourteen genes related to ageing in BM-MSCs were associated with the prognosis of MM, and by combining this genotypic information with clinical factors, a promising clinical prognostic model was established.

NOVEL MUTATIONS IN THE WNT1, TMEM38B, P4HB, AND PLS3 GENES IN FOUR UNRELATED CHINESE FAMILIES WITH OSTEOGENESIS IMPERFECTA.

OBJECTIVE: Osteogenesis imperfecta (OI) is a group of heritable fragile bone diseases, and the majority are caused by pathogenic variants in the COL1A1 and COL1A2 genes. We sought to identify the genetic causes and phenotypes of OI in Chinese patients without COL1A1 or COL1A2 mutations. METHODS: Twenty-three patients who were diagnosed with sporadic OI but did not carry COL1A1/2 mutations were recruited, and their genomic DNA was analyzed using targeted next-generation sequencing of rare OI-related genes. The resulting damaging mutations in the probands and their parents were verified using Sanger sequencing. Moreover, the efficacy of long-term bisphosphonate treatment was evaluated in proband 1. RESULTS: Compound heterozygous variants in the WNT1 and TMEM38B genes were identified in proband 1 and proband 2, respectively. A heterozygous mutation in the P4HB gene was identified in proband 3, and a hemizygous mutation in PLS3 was identified in proband 4. The unaffected parents of the probands (except the father of proband 4) with mutations in the WNT1, TMEM38B, and PLS3 genes were heterozygous carriers of each of the variants, respectively. Notably, proband 3 had the characteristic exophthalmos, flat nasal bridge and flat, wide forehead. None of the patients presented with dentinogenesis imperfecta or hearing loss. Furthermore, bisphosphonates exerted beneficial effects on proband 1, who carried the WNT1 mutations, by increasing bone mineral density Z-score, reshaping the compressed vertebrae and decreasing the fracture risk. CONCLUSION: We identified novel mutations and expanded the spectrum of phenotypes and genotypes of the extremely rare disorder OI. ABBREVIATIONS: BMD = bone mineral density; MIM = Mendelian Inheritance in Man; OI = osteogenesis imperfecta; PDI = protein disulfide isomerase.

Identification of a novel mutation of the NTRK1 gene in patients with congenital insensitivity to pain with anhidrosis (CIPA).

INTRODUCTION: Congenital insensitivity to pain with anhidrosis (CIPA) is a rare autosomal recessive disorder resulting from NTRK1 mutation. Over 105 NTRK1 mutations have been reported in CIPA patients worldwide. The causative NTRK1 mutations lead to loss of function of the TrkA protein, an important ligand for nerve growth factor (NGF), and therefore induce various clinical phenotypes associated with neuron maturation defects. MATERIALS AND METHODS: Three patients from unrelated families with CIPA were subjected to detailed clinical examinations. Blood samples were collected from all the patients and their available family members, as well as 200 healthy volunteers. Sanger sequencing for all the exons and splicing sites of NTRK1 was performed on all samples. The phenotype-genotype relationship and genetic epidemiology of Chinese CIPA patients were also analysed. RESULTS: A total of four different NTRK1 mutations [c.851-33T>A, c.44G>A (p.Trp15*), c.287+2dupT, c.1549G>C (p.Gly517Arg)] were identified in these families, and c.1549G>C (p.Gly517Arg) was a novel mutation that had not been reported previously. The 'mild' manifestations observed in patients with c.851-33T>A indicated this mutation as a 'mild' mutation. After reviewing studies reporting mutations in Chinese CIPA patients, we speculate the mutation c.851-33T>A is one of the founder mutations in the Chinese population. CONCLUSIONS: Our research expanded the spectrum of the NTRK1 mutations associated with CIPA patients, provided additional clues relating to the phenotype-genotype relationship in CIPA, and summarized the features of the genetic epidemiology of CIPA in the Chinese ethnic group.